92 citations
- Ludwig-Maximilians-Universität MünchenDE9 papers
- Darmstadt University of Applied SciencesDE6 papers
- Munich Center for Machine Learning6 papers
- LMU KlinikumDE3 papers
- University College LondonGB3 papers
- Zimmer Biomet (Netherlands)NL3 papers
- Fraunhofer Institute for Computer Graphics ResearchDE2 papers
- Joint Research CentreNL2 papers
- Medical University of ViennaAT2 papers
- MRC Clinical Trials Unit at UCLGB2 papers
- Ruhr University BochumDE2 papers
- Technical University of MunichDE2 papers
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stat.AP2024
To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism
Milena Wünsch, Christina Sauer, Moritz Herrmann +2
Gene set analysis, a popular approach for analysing high-throughput gene expression data, aims to identify sets of genes that show enriched expression patterns between two conditio…
stat.AP2023★ 7 cited
From RNA sequencing measurements to the final results: a practical guide to navigating the choices and uncertainties of gene set analysis
Milena Wünsch, Christina Sauer, Patrick Callahan +2
Gene set analysis, a popular approach for analyzing high-throughput gene expression data, aims to identify sets of related genes that show significantly enriched or depleted expres…
stat.AP2022★ 10 cited
Statistical modelling of COVID-19 data: Putting Generalised Additive Models to work
Cornelius Fritz, Giacomo De Nicola, Martje Rave +5
Over the course of the COVID-19 pandemic, Generalised Additive Models (GAMs) have been successfully employed on numerous occasions to obtain vital data-driven insights. In this pap…